An ensemble approach to deep‐learning‐based wireless indoor localization

Abstract The authors investigate the use of deep learning in wireless indoor localization to address the shortcomings of the existing range‐based (e.g. trilateration and triangulation) and range‐free (e.g. fingerprinting) localization. Instead of relying on geometric models and hand‐picked features,...

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Библиографические подробности
Главные авторы: Juthatip Wisanmongkol, Attaphongse Taparugssanagorn, Le Chung Tran, Anh Tuyen Le, Xiaojing Huang, Christian Ritz, Eryk Dutkiewicz, Son Lam Phung
Формат: Artigo
Язык:Inglês
Опубликовано: Wiley 2022-04-01
Серии:IET Wireless Sensor Systems
Предметы:
indoor communication
indoor navigation
indoor radio
RSSI
learning (artificial intelligence)
Online-ссылка:https://doi.org/10.1049/wss2.12035
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